pltnts <- list.files("~/R/terni/rds", pattern = "^[M-Z]", full.names = TRUE)
map(pltnts, \(pltnt) {
inquinante <- tools::file_path_sans_ext(basename(pltnt))
cat("\n## ", inquinante, "\n\n")
df <- read_csv("~/R/terni/data/dataframes/df_finale.csv", show_col_types = FALSE)
index <- grep(inquinante, names(df))
names(df)[index] <- "value"
rds <- readRDS(pltnt)
mod <- getModel(names(rds), df)
gamtabs(mod, type = "HTML")
cat("\n\n")
cat("R²:", summary(mod)$r.sq %>% round(3) )
cat("\n\n")
# stargazer(mod, type="text" )
appraise(mod) %>% print()
draw(mod) %>% print()
rm(mod)
cat("\n\n")
})
Mg_i
stringa modello: gam(log(value) ~ s(nirradiance_IQR) + s(pblmin_median,
k=3) + s(sp_IQR) + s(v10m_min) , gamma=1.4, family=gaussian(link=log),
data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.3775
|
0.0049
|
283.4954
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(nirradiance_IQR)
|
2.4391
|
2.8824
|
12.5031
|
< 0.0001
|
|
s(pblmin_median)
|
1.0000
|
1.0000
|
23.8863
|
< 0.0001
|
|
s(sp_IQR)
|
1.0001
|
1.0001
|
132.3558
|
< 0.0001
|
|
s(v10m_min)
|
1.0000
|
1.0000
|
6.7063
|
0.0101
|
R²: 0.425


Mg_s
stringa modello: gam(log(value) ~ s(pbl00_max) + s(scrapyard) +
s(wspeed_max_mean) + s(s3_sup_200) + s(s6_sup_200) , gamma=1.4,
family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.4034
|
0.0042
|
332.7256
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pbl00_max)
|
4.8392
|
5.4881
|
22.2652
|
< 0.0001
|
|
s(scrapyard)
|
1.4159
|
1.7132
|
24.7618
|
< 0.0001
|
|
s(wspeed_max_mean)
|
2.7679
|
3.1948
|
6.2116
|
0.0003
|
|
s(s3_sup_200)
|
1.9556
|
2.3266
|
3.4066
|
0.0276
|
|
s(s6_sup_200)
|
1.0001
|
1.0002
|
6.0819
|
0.0143
|
R²: 0.509


Mn_i
stringa modello: gam(log(value) ~ s(s3_sup_200) + s(wdir_IQR) +
s(nirradiance_max) + s(cold_area) + s(pblmin_median, k=3) , gamma=1.4,
family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.7850
|
0.0082
|
95.3319
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(s3_sup_200)
|
7.6200
|
7.7565
|
19.5202
|
< 0.0001
|
|
s(wdir_IQR)
|
1.0000
|
1.0000
|
60.7915
|
< 0.0001
|
|
s(nirradiance_max)
|
1.0000
|
1.0000
|
29.9658
|
< 0.0001
|
|
s(cold_area)
|
7.4337
|
8.1583
|
5.4911
|
< 0.0001
|
|
s(pblmin_median)
|
1.0000
|
1.0000
|
5.7412
|
0.0173
|
R²: 0.653


Mn_s
stringa modello: gam(log(value) ~ s(pbl12_mean) + s(scrapyard) +
s(nirradiance_IQR) + s(wspeed_max) + s(s7_sup_200, k=3) + s(s6_sup_200)
+ s(cold_area) + s(pwspeed_max) , gamma=1.4, family=gaussian(link=log),
data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.5601
|
0.0114
|
49.0079
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pbl12_mean)
|
1.0000
|
1.0001
|
100.1215
|
< 0.0001
|
|
s(scrapyard)
|
1.0000
|
1.0000
|
44.9631
|
< 0.0001
|
|
s(nirradiance_IQR)
|
2.3936
|
2.7712
|
67.2165
|
< 0.0001
|
|
s(wspeed_max)
|
0.9928
|
1.2275
|
1.8230
|
0.2093
|
|
s(s7_sup_200)
|
1.0000
|
1.0000
|
6.0225
|
0.0148
|
|
s(s6_sup_200)
|
1.1998
|
1.3712
|
9.0031
|
0.0031
|
|
s(cold_area)
|
1.0000
|
1.0000
|
13.4237
|
0.0003
|
|
s(pwspeed_max)
|
1.9928
|
2.2275
|
2.2804
|
0.1033
|
R²: 0.705


Mo_i
stringa modello: gam(log(value) ~ s(pblmax_min) + s(cold_area) +
s(s1_sup_200, k=7) , gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-0.2418
|
0.0974
|
-2.4819
|
0.0137
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pblmax_min)
|
7.8757
|
8.3728
|
22.1125
|
< 0.0001
|
|
s(cold_area)
|
2.8465
|
3.5748
|
26.8501
|
< 0.0001
|
|
s(s1_sup_200)
|
1.7710
|
1.9837
|
5.6332
|
0.0028
|
R²: 0.668


Mo_s
stringa modello: gam(log(value) ~ s(cold_area) + s(nirradiance_mean) +
s(s3_sup_200) + s(pblmin_median, k=3) + s(m_dis_ferr) + s(pbl00_mean) ,
gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.4577
|
0.0168
|
27.2783
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(cold_area)
|
3.5956
|
4.3740
|
34.6549
|
< 0.0001
|
|
s(nirradiance_mean)
|
2.6442
|
3.2531
|
33.3174
|
< 0.0001
|
|
s(s3_sup_200)
|
7.5440
|
7.8310
|
14.9215
|
< 0.0001
|
|
s(pblmin_median)
|
1.0000
|
1.0000
|
27.9580
|
< 0.0001
|
|
s(m_dis_ferr)
|
1.0001
|
1.0002
|
11.5412
|
0.0008
|
|
s(pbl00_mean)
|
1.0000
|
1.0000
|
9.5925
|
0.0022
|
R²: 0.755


Na_i
stringa modello: gam(log(value) ~ s(pwspeed_min, k=7) + s(v10m_mean) +
s(tmax2m_IQR) , gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.7114
|
0.0048
|
360.1878
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pwspeed_min)
|
1.0000
|
1.0001
|
61.0800
|
< 0.0001
|
|
s(v10m_mean)
|
1.0000
|
1.0000
|
18.3960
|
< 0.0001
|
|
s(tmax2m_IQR)
|
1.0000
|
1.0000
|
8.6452
|
0.0036
|
R²: 0.203


Na_s
stringa modello: gam(log(value) ~ s(u10m_IQR) + s(s7_sup_200, k=3) ,
gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.7578
|
0.0035
|
505.0096
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(u10m_IQR)
|
8.0000
|
8.0000
|
39.9308
|
< 0.0001
|
|
s(s7_sup_200)
|
1.8868
|
1.9872
|
5.6379
|
0.0044
|
R²: 0.562

Nb_i
stringa modello: gam(log(value) ~ s(rh_min) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-23.4201
|
969820731.2887
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(rh_min)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

Nb_s
stringa modello: gam(log(value) ~ s(v10m_min) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.6778
|
916551596.4583
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(v10m_min)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004


Ni_i
stringa modello: gam(log(value) ~ s(cold_area) + s(wdir_IQR) +
s(s6_sup_200) + s(s1_sup_200, k=7) + s(wdir_median) + s(t2m_IQR) +
s(sp_mean) , gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.8086
|
0.0120
|
67.2528
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(cold_area)
|
4.7186
|
5.5927
|
57.8875
|
< 0.0001
|
|
s(wdir_IQR)
|
1.0000
|
1.0000
|
47.3159
|
< 0.0001
|
|
s(s6_sup_200)
|
6.9075
|
7.7226
|
6.2336
|
< 0.0001
|
|
s(s1_sup_200)
|
1.3748
|
1.5519
|
4.1753
|
0.0135
|
|
s(wdir_median)
|
1.0000
|
1.0000
|
29.2577
|
< 0.0001
|
|
s(t2m_IQR)
|
1.0000
|
1.0000
|
10.7289
|
0.0012
|
|
s(sp_mean)
|
1.0000
|
1.0000
|
7.1496
|
0.0080
|
R²: 0.722

Ni_s
stringa modello: gam(log(value) ~ s(m_dis_ferr) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-2171.6198
|
822.9713
|
-2.6388
|
0.0088
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(m_dis_ferr)
|
1.0000
|
1.0000
|
6.9647
|
0.0088
|
R²: 0.231


Pb_i
stringa modello: gam(log(value) ~ s(nirradiance_mean) + s(s3_sup_200) +
s(wspeed_IQR) + s(wspeed_max_max) + s(wspeed_max_min) + s(wdir_IQR) ,
gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.3775
|
0.0140
|
26.9697
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(nirradiance_mean)
|
1.0000
|
1.0000
|
32.1711
|
< 0.0001
|
|
s(s3_sup_200)
|
7.4182
|
7.8474
|
28.0831
|
< 0.0001
|
|
s(wspeed_IQR)
|
1.0000
|
1.0000
|
0.2321
|
0.6304
|
|
s(wspeed_max_max)
|
2.3873
|
2.8503
|
6.3126
|
0.0006
|
|
s(wspeed_max_min)
|
1.0000
|
1.0000
|
12.3599
|
0.0005
|
|
s(wdir_IQR)
|
1.0000
|
1.0000
|
6.7340
|
0.0100
|
R²: 0.673

Pb_s
stringa modello: gam(log(value) ~ s(sp_min) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.7611
|
2017.3248
|
-0.0113
|
0.9910
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(sp_min)
|
1.0000
|
1.0001
|
0.0005
|
0.9891
|
R²: 0.237


PM10
stringa modello: gam(log(value) ~ s(v10m_min) + s(pwspeed_IQR) +
s(v10m_median, k=9) + s(pop_200) , gamma=1.4, family=gaussian(link=log),
data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.2172
|
0.0039
|
314.5843
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(v10m_min)
|
2.0134
|
2.3286
|
21.4008
|
< 0.0001
|
|
s(pwspeed_IQR)
|
3.9684
|
4.4831
|
68.1847
|
< 0.0001
|
|
s(v10m_median)
|
1.0001
|
1.0002
|
24.7028
|
< 0.0001
|
|
s(pop_200)
|
1.0001
|
1.0001
|
6.1866
|
0.0135
|
R²: 0.754

Rb_i
stringa modello: gam(log(value) ~ s(pblmin_IQR, k=9) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-23.8260
|
713180328.4144
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pblmin_IQR)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

Rb_s
stringa modello: gam(log(value) ~ s(tmax2m_mean) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-9.6249
|
9.3176
|
-1.0330
|
0.3025
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(tmax2m_mean)
|
1.2578
|
1.4561
|
0.8830
|
0.2305
|
R²: 0.323

Sb_i
stringa modello: gam(log(value) ~ s(rh_max) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-131.5374
|
349025.3924
|
-0.0004
|
0.9997
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(rh_max)
|
1.0001
|
1.0002
|
0.0001
|
0.9955
|
R²: 0.124

Sb_s
stringa modello: gam(log(value) ~ s(tmin2m_IQR) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-24.6092
|
1429869567.4169
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(tmin2m_IQR)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004


Sn_i
stringa modello: gam(log(value) ~ s(pbl12_mean) + s(hot_area) +
s(s4_sup_200) + s(s8_sup_200) , gamma=1.4, family=gaussian(link=log),
data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-0.3424
|
0.0494
|
-6.9266
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pbl12_mean)
|
1.0000
|
1.0000
|
332.2339
|
< 0.0001
|
|
s(hot_area)
|
2.1122
|
2.6346
|
19.1946
|
< 0.0001
|
|
s(s4_sup_200)
|
1.0001
|
1.0001
|
7.2134
|
0.0077
|
|
s(s8_sup_200)
|
1.6335
|
2.0390
|
5.9573
|
0.0029
|
R²: 0.779

Sn_s
stringa modello: gam(log(value) ~ s(pblmin_median, k=3) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-23.0719
|
467030630.5307
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pblmin_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004


Sr_i
stringa modello: gam(log(value) ~ s(tp_IQR) , gamma=1.4,
family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-2.9084
|
5.5494
|
-0.5241
|
0.6006
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(tp_IQR)
|
7.0532
|
7.1164
|
3.4669
|
0.0007
|
R²: 0.441


Sr_s
stringa modello: gam(log(value) ~ s(v10m_median, k=9) + s(imp_200) ,
gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-1.6333
|
102.5148
|
-0.0159
|
0.9873
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(v10m_median)
|
7.0000
|
7.0001
|
23.6825
|
< 0.0001
|
|
s(imp_200)
|
1.0000
|
1.0000
|
6.9530
|
0.0089
|
R²: 0.61


Ti_i
stringa modello: gam(log(value) ~ s(rh_max) + s(pop_200) + s(pblmin_IQR,
k=9) + s(s3_sup_200) + s(s4_sup_200) , gamma=1.4,
family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
0.4315
|
0.0140
|
30.7584
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(rh_max)
|
3.1428
|
3.8193
|
39.0249
|
< 0.0001
|
|
s(pop_200)
|
6.4832
|
7.1177
|
8.2150
|
< 0.0001
|
|
s(pblmin_IQR)
|
1.0001
|
1.0001
|
42.6792
|
< 0.0001
|
|
s(s3_sup_200)
|
3.8167
|
4.1252
|
4.0033
|
0.0017
|
|
s(s4_sup_200)
|
1.0001
|
1.0001
|
17.1647
|
< 0.0001
|
R²: 0.528

Ti_s
stringa modello: gam(log(value) ~ s(u10m_mean) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-23.7015
|
1110537246.7412
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(u10m_mean)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

Tl_i
stringa modello: gam(log(value) ~ s(s5_sup_200, k=9) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.8890
|
910243221.4849
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(s5_sup_200)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

Tl_s
stringa modello: gam(log(value) ~ s(s3_sup_200) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.5587
|
419614258.4032
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(s3_sup_200)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

U_i
stringa modello: gam(log(value) ~ s(kndvi) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.2572
|
573815329.4478
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(kndvi)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

U_s
stringa modello: gam(log(value) ~ s(tp_median, k=3) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.2573
|
670082786.1382
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(tp_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

V_i
stringa modello: gam(log(value) ~ s(tmin2m_IQR) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-24.8338
|
1374423269.9621
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(tmin2m_IQR)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

V_s
stringa modello: gam(log(value) ~ s(t2m_min) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
## Warning in newton(lsp = lsp, X = G$X, y = G$y, Eb = G$Eb, UrS = G$UrS, L = G$L,
## : Adattamento terminato con errore di passo: controllare attentamente i
## risultati
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-42.5595
|
68.3869
|
-0.6223
|
0.5342
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(t2m_min)
|
1.0000
|
1.0000
|
0.3700
|
0.5435
|
R²: 0.131

W_i
stringa modello: gam(log(value) ~ s(u10m_median, k=9) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.5540
|
418208955.1281
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(u10m_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

W_s
stringa modello: gam(log(value) ~ s(u10m_median, k=9) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.7686
|
503187178.7599
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(u10m_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004


Zn_i
stringa modello: gam(log(value) ~ s(wdir_mean) + s(nirradiance_max) ,
gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.2598
|
0.0071
|
176.2748
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(wdir_mean)
|
6.8044
|
7.6989
|
22.9497
|
< 0.0001
|
|
s(nirradiance_max)
|
1.0001
|
1.0002
|
3.0862
|
0.0801
|
R²: 0.41


Zn_s
stringa modello: gam(log(value) ~ s(nirradiance_mean) + s(scrapyard) +
s(v10m_IQR) , gamma=1.4, family=gaussian(link=log), data =
df)
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
1.1164
|
0.0075
|
148.6038
|
< 0.0001
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(nirradiance_mean)
|
4.9428
|
5.4388
|
51.9507
|
< 0.0001
|
|
s(scrapyard)
|
3.2254
|
4.0040
|
9.9808
|
< 0.0001
|
|
s(v10m_IQR)
|
3.0812
|
3.6322
|
26.1013
|
< 0.0001
|
R²: 0.754

Zr_i
stringa modello: gam(log(value) ~ s(sp_median) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-24.5748
|
935817661.1736
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(sp_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004

Zr_s
stringa modello: gam(log(value) ~ s(pbl00_median, k=6) , gamma=1.4,
family=gaussian(link=log), data = df)
## Warning in log(mu): Si è prodotto un NaN
|
A. parametric coefficients
|
Estimate
|
Std. Error
|
t-value
|
p-value
|
|
(Intercept)
|
-22.7011
|
677221618.5782
|
-0.0000
|
1.0000
|
|
B. smooth terms
|
edf
|
Ref.df
|
F-value
|
p-value
|
|
s(pbl00_median)
|
1.0000
|
1.0000
|
0.0000
|
1.0000
|
R²: -0.004


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